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By John T. Crawford

Open pit limit analysis techniques of various types have been utilized for many years to design ultimate pit surfaces. In the last 15 years there have been many advances in the development of sophisticated computer methods to aid this process. The extensive capability of the computer has led to multiple alternative approaches to problem solving. Computerized open pit limit analysis methods can be applied to a broad scope of long-range and intermediate-range mine planning and design questions. A single computer run develops a pit design from a set of data. A set of nonsequential runs is used to evaluate changes in pit slopes, property restraints, and mineral model variables. Ore reserve economic sensitivity and intermediate-range mining plans can be developed using sequential computer runs. Present value methods are incorporated by using iterative sequential techniques. Multiple ore processes, dump leaching credits, and the trade-off between open pit and underground mining can also be handled. Many of the applications described are representative of current practice. The remainder are suggested extensions.

Jan 1, 1979

By M. Ataee-pour, S. E. Jalali

So far, a large number of algorithms have been developed for the optimization of pit limits, most of which follow deterministic rules. In this paper, a new algorithm is introduced, which follows a probabilistic logic using the Markov chain process. The algorithm is implemented on a transition matrix that corresponds to the 2D conventional economic block model of the mining area. The probability of mining a block is proportional to the desirability it may provide. Applying this algorithm, the probability of mining each block is obtained, and finally, the optimum pit limits are defined as the pit, which provides the highest probability of mining. In order to validate the proposed model, a numerical example is given and the results of the algorithm are compared to those of a dynamic programming algorithm. A 2D analysis of the problem is discussed in this paper. Although dealing with 3D problems requires larger size matrices, the optimization method is the same and the algorithm does not need any smoothing.

Jan 1, 2006

By F. Seymour

A modified 3D Lerchs-Grossmann (LG) graph tree algorithm is presented that generates the complete set of nested maximum valued pits in a single run. This modified LG algorithm looks at the relative strength (average value) of the branches (groups of blocks). Pointers are allocated and pruned until there are no members of weaker (lower average value) branches overlying members of stronger (higher aver-age value) branches. The final set of strong branches are listed in order of decreasing strength. The pits they represent form the maximum valued convex hull for a single variable pit limit parameterization. A description of the algorithm is given along with examples of how it has been applied at Newmont.

Jan 1, 1995

By R. M. (Mike) Robb

Introduction The requirements to investigate a wide range of alternatives and analyze a variety of ‘what if’ questions make the automation of pit design a requirement in today’s rapidly changing mining industry. The wide-spread application of computers has relieved the engineer of much of the tedious and error-prone work related to mine design. He is thus free to do the creative and innovative thinking for which he is trained. It is now possible to investigate a large number of alternative pit designs in a reasonably short time period. In the past it was very easy for a team of engineers to consume 12 to 14 man-months in the detailed hand design of a large open pit. The pressure of today's mining industry, the desire to investigate a variety of alternative designs, and the shortage of qualified engineers make the slowness of hand design less preferred.

Jan 1, 1979

By Benjamin C. Koskiniemi

Introduction When evaluating any ore body, one of the first questions concerns the ore reserves. In the case of an open pit mine, this is not possible to answer reliably until the ultimate (final) pit limits have been established. Techniques used in designing an ultimate pit are classed as (1) manual, (2) computer, and (3) combined manual-computer. This chapter will describe how manual techniques can be utilized in designing an ulti¬mate pit Certain economic and design criteria must be established before the actual design begins In order to begin designing an ultimate pit, it will be assumed that the engineer already has the following data available (1) vertical sections, (2) horizontal sections for each level, (3) stripping curve, (4) bench height, (5) bank slope angle between levels, (6) level berm width, (7) roadway width, (8) pit slope angles at ultimate pit limits (estimated average including roads and ramps and between roads and ramps), and (9) minimum width of pit bottom

Jan 1, 1979

By Dermot M. Ross-Brown

Introduction Slope angles are one of the major factors affecting the shape of the final pit and the location of the walls Due to differences in geology, the optimum slope angles vary from pit to pit and within different parts of the same pit. Indeed, it is not unusual to have different slope angles for the top and bottom portions of the same cross section. The optimization of these slope angles is a major study in itself and this chapter is intended as a general introduction to the subject. It is not intended to be a comprehensive text for the absolute beginner The objective is to put the various aspects of slope stability analysis into relative perspective by describing the vari¬ous analytical techniques available and indicating when each may be most appropriately used References are made to the many excellent texts and papers on slope stability for the reader who does not have a formal training in soil or rock mechanics. In writing this chapter, an assumption has been made that a tentative mining plan has been drawn up, includ¬ing a preliminary estimate of the slope angles. It has also been assumed that all the necessary field and laboratory data has been collected and reduced to a form suitable for input into the stability analyses.

Jan 1, 1979

By Ben L. Seegmiller

Introduction The profitability of an open pit operation depends to a large extent on the use of the steepest pit slopes possible, provided they do not fail during the life of the mine Optimum pit slopes can be designed by using rock mechanics technology. Such technology includes gathering and analyzing pertinent data prior to pit design, rigorous application of rock mechanics principles during the design process, remedial actions to improve slope stability, and monitoring slopes during the life of the mine. Ignoring rock mechanics technology in pit design may place the entire mining enter- prise in jeopardy Disruption of mining operations and safety hazards caused by slope instability can be severe. A classic case in point is the major slope failure (Seegmiller, 1972) that occurred at a southwestern US copper mining operation in 1970-1971 Minor slope stability problems initially amounted to no more than a nuisance, but in time, the unstable zones became larger, causing greater disruption of production and threatening safety Mining at or near the slide toe had continued throughout the period of slope failure, aggravating the already unstable condition The original plan for this pit called for mining the overall pit slope to 37.5" Mine operators were forced to lessen the back- slope angle in the hope that the failing rock mass would stabilize. However, stabilization did not take place, and when mining in the area of failure was completed, the overall slope had been reduced to approximately 27" Mining had been successful in removing only a small portion of the ore body at a high stripping ratio.

Jan 1, 1979

By C. A. Lorenson

THE Marmoraton mine is located a mile southeast of Marmora, a village in Hastings county, Ontario, 130 miles east from Toronto and 143 miles west of Ottawa. Highway No. 14 from Belleville intersects Highway No. 7 at Marmora and the branch line of the Canadian National railway between Trenton and Bancroft passes through the property just east of the open pit. HISTORY AND GEOLOGY The Marmora orebody appears as the whorls of a thumb print on the aeromagnetic survey map released by the Ontario Department of Min.es early in 1950, the survey of the district having been made in 1948 and 1949, under the joint auspices of the Department of Mines and the Geological Survey of Canada. The 'anomaly' appeared to have interesting possibilities, so Bethlehem representatives carried out a ground survey and began drilling the property in June, 1950. A total of 40 holes, aggregating 37,000 feet, were drilled to delineate the ore-body. The Marmora orebody is a re-placement of Precambrian limesto.ne with zones or bands of magnetite interlaid with metamorpl1ic rocks and cut by later intrusives. The ore and associated Precambrian rocks are overlain by 100 to 150 feet of flat-lying Palaeozoic limestone. It is a low-grade deposit averaging 33 per cent iron and requires concentration to raise it to 65 per cent iron grade.

Jan 1, 1958

By Tyler Acorn, Brandon Wilson, Jeff Boisvert

Project-scale decisions in surface mining operations rely on the optimization and subsequent evaluation of pit limits. This process ignores the ability for mine plans to adapt as more information is gathered. Stochastic methods, which consider uncertainty in the pit optimization, generally act to refine the boundaries of the pit on a fine scale. This paper extends uncertainty-based methods to consider unique scenarios through a clustering of the realizations that are being optimized. This results in the generation of multiple sets of similar realizations. A separate pit is optimized on each set of realizations, resulting in the production of a series of planning scenarios. This accounts for the adaptability of mine planning as more information is gained. A decision-making framework is then applied to the resulting scenario plans to select the optimal choice. The improvements stem from the joint uncertainty considered when realizations are grouped that is not considered when the probability of a block being in any optimized pit is considered. Mining operations today can benefit from considering additional planning options as identified and evaluated in this workflow.

By Tyler Acorn, Brandon Wilson, Jeff Boisvert

Scenario-level uncertainty is a representation of large-scale differences encountered when considering ultimate mining pits optimized over various subsets of stochastic realizations. Accounting for scenario-level uncertainty allows mine plans to be assessed against several probabilistic subsurface interpretations. Scenario-level uncertainty is found through clustering stochastic geostatistical realizations and optimizing final pits across the realizations in each cluster. Where these pits are geometrically different, plans for each scenario differ. Knowing these differences allows the value of each planning alternative to be assessed based on the value and relative probability of each scenario. These results also facilitate the use of formal decision-making frameworks for planning, leading to optimization that better represents the full statistical characterization of the deposit. An example utilizing this approach evaluates both infrastructure placement and drilling program requirements. In both cases, scenario-level uncertainty improves initial plans by limiting opportunity costs and identifying additional potential.

By Gordon S. Thomas

The problem of how best to exploit a reserve has vexed mine planners and design engineers since mining began. The cyclic nature of the mine design-scheduling problem, combined with the lack of good mathematical tools for tackling it, have ensured that it has been, and will continue to be, a major challenge for operations researchers working in mining. This paper reviews the current state of the art in pit optimisation and scheduling algorithms. Starting from the inception of the first block models in the late 1950's, it progresses through the developments and applications of the Moving Cone algorithm, the Lerchs Grossmann 3D Graph Theory algorithm and some of the heuristics, to the new artificial intelligence techniques that are being applied today. Along the way, it discusses the limitations of the various approaches and lays the foundations for the research that is currently being undertaken by CSIRO and others in the field of mine production scheduling and control.

Jan 1, 1996

By Damon H. McFadden

5.1-1. Geographic and Geologic Factors. Surface mines are located where the coal seam can be economically uncovered and where the product can be utilized competitively with other fuels. The planning and designing of a pit may follow various procedures. The sequence for consideration of the influential factors as considered here may not be complete for every pit, nor will it be necessary to be completely used in each design. It is suggested as a check and outline for the engineering approach. Controlling conditions for the layout should be listed and considered with the facilities and equipment for the exploitation. After these items, as listed below, have been discussed and the feasibility agreed upon, then the actual planning and design of the pit can be done. GEOGRAPHIC FEATURES. The location of the coal area sets the climatic stage. The rainfall, the temperature extremes, and the general weather conditions all affect the design of the pit. Overburden soil when wet may not be stackable and may be impossible to move by standard procedures. The coal seam itself may be so soft that it must not be traveled on when wet, as the losses may be the difference between a profitable venture and an unsuccessful one. Some equipment will work well on dry soil only, just as a dredge works only in the wet. The conditions must be checked and analyzed. Some equipment cannot handle frozen soil (wheel excavators), so temperature extremes must be noted. The extreme weather conditions may also govern the expected working days and therefore the ultimate production. The altitude (atmospheric pressure) may affect the equipment, and this should be checked. All of these conditions should be noted on the preliminary map of the area. GEOLOGIC FACTORS. The geologic and surface conditions of the coal field dictate the type of pit generally feasible. Rough terrain, rolling terrain,

Jan 1, 1968

By Donald O. Rausch, Adolph Soderberg

4.1-1. Introduction. Open pit mine planning must be correlated to all phases of a mining operation. The factors that must be considered in planning an open pit mine are numerous and must reflect the characteristics and surrounding conditions of a particular orebody. Therefore, only an outline of the subject can be presented here to aid the planning engineer in pointing out procedures that are generally applicable to pit design. The presentation is directed toward the planning of an open pit copper mine, but the procedures discussed should apply in most cases to any type of metallic or nonmetallic orebody. In planning an open pit mine the pertinent elements that must be included are: assays, geology, tonnage and areal extent of ore reserves, topography, mining equipment, economic factors of operating costs, capital expenditures, profit, types of ore, pit limits, cut-off grade, stripping ratio, rate of production, pit slopes, bench heights, road grades, ore metallurgical characteristics, hydrological conditions, property lines, and marketing considerations. 4.1-2. Sampling. Sampling must be adequate to classify the various materials to be removed from an open pit mine. Drillhole assays are plotted on sections and plan maps with ore and waste blocked out by selected bench intervals. These maps are prepared to depict the geological and other conditions existing on each mine level. The confidence factor to be applied to sampling and the resultant assays values must be given careful consideration. In uniformly disseminated de- posits, the confidence factor will approach unity. For widely fluctuating values, the average assay values should be discounted somewhat, the degree depending upon such factors as drillhole spacing. Such samples, at best, represent a very few pounds for hundreds to thousands of tons of ore

Jan 1, 1968

By T D. Sullivan

Risk lies at the heart of all mining and nowhere more so than in pit slope design. Mining is principally about two areas of risk; safety and economics. This paper addresses the main elements of pit slope design and presents a view of the state of the art in terms of safety, design, prediction of performance, success and pit slope management. There has been a recent trend for serious injury and fatalities due to stability in open pit mines. The causes and contributing factors are analysed in relation to geotechnical knowledge, pit slope design and management. Currently there is no standard classification system for mine slope designs and it is considered doubtful if a universal system is possible. Designs are usually formulated in accordance with many different methodologies, various engineering principals and a number of different philosophical approaches, with results often presented in terms of Factors of Safety or Probabilities of Failure. However wide experience has demonstrated that even with apparently detailed engineering investigation and analysis at Feasibility Level, at the Operating Stage mine slope angles are regularly subject to large changes. The general experience is that these changes are ± 5° and 16° overall, which is considerably outside the accepted order of accuracy. For large deep mines these are huge changes and represent significant risks to the operations. The current state of practice in pit slope design is examined for two stages, feasibility and operating.

Jan 1, 2006

By J. Geyer, B. T. Burton, H. W. Newcomen

For open pits developed in tropical climates the upper portions of the pit walls are often located in residual soils and weathered rock. Due to the presence of relict structures, and the relatively low strength of the residual soils and weathered rock, design slope angles in these materials have to be developed by blending the results of kinematic assessments of geologic structures with rock mass stability analyses and traditional soil mechanics. Background information on the engineering considerations of residual soils are discussed, and the results of geotechnical assessments for proposed pit design of the Brisas del Cuyuni Project, located in southeastern Venezuela, are presented.

Jan 1, 2000

It is often assumed that geotechnical investigations or studies for open pit mines are confined to providing a slope design. However in an operating mine, the design is only one component of a mine geotechnical program. Reviews of slope designs are ongoing throughout the mine life. The concept of Pit Slope Management has been formulated because the design only entails one component of a total program that contributes to a safe, efficient mining operation. Risk is a normal part of mining. Effective management allows the risk to be contained or controlled. If the slopes are not effectively managed there will be increased risk for the operation. Experience has shown that utilisation of Pit Slope Management coupled with a broad base of experience to define the key controls on stability, provides a pro-active, objective approach. The reasoning is deductive and relies on the behaviour of the ærocksÆ. Once the key aspects are defined, studies are well focused, implemented as required and the risks can be effectively managed. When the key controls on stability are poorly understood reasoning is typically more ægut feelÆ. Under such circumstances studies, if carried out, may meet short-term objectives but often ignore the long-term objectives. Hence the risk to the project is greatly increased. This paper presents several case studies highlighting the above aspects and present elements of the Pit Slope Management Program approach which have been successfully utilised by the author to manage risk in mining projects.

Jan 1, 2003

By W. C. Goldberg, E. M. Frizzell

Monitoring slope displacement in open-pit mines can help predict collapses and prevent serious damage, injuries, and fatalities. Early detection of movement may indicate the need to modify slope geometry, initiate dewatering if the slope is wet, or consider artificial support measures such as cable bolting. Slope monitoring at the Berkeley pit was carried out with varying degrees of intensity and continuity for about 15 years. Some of the old mine records are still intact and accessible. Slope monitoring data can therefore be collected and published for the benefit of other mine operators. Because prediction of slope failures is empirical in nature, publication of several well documented case studies will be a valuable contribution to the industry. Background - Berkeley pit Open-pit mining of copper from the Berkeley pit, located on the east side of Butte, MT, began in 1955 and ceased in 1982. During that time, about 1 Gt (1.2 billion st) of material were removed to form a pit about 1.8 km wide by 2.1 km long (6000 ft by 7000 ft) at the rim, and 550 m (1800 ft) deep as measured from the high hill on the northwest side. From the south side, the pit only measures 365 m (1200 ft) deep. The Berkeley pit was first owned and operated by Anaconda Minerals Co., and subsequently by Arco. Following its closure in April 1982, the mine began to fill with water. Washington Construction purchased the property in 1986, and Montana Resources Inc. began mining to the east of the Berkeley pit in July 1986. Numerous instances of slope failure were recorded during the course of mining and several intensive geotechnical investigations were conducted in an effort to optimize the mine design. One of the last and most comprehensive studies was initiated in 1977. For purposes of geotechnical analysis, the mine was divided into nine design sectors on the basis of geologic conditions, geographic orientation, and economic importance (Fig. 1). Only two of these sectors - the concentrator and the southeast corner - are considered here. Material properties were obtained from several studies of samples collected from the mine and adjacent areas. The slope was monitored using standard surveying techniques to record the amount of movement in an area. The

Jan 1, 1989

By R. B. Moffitt

INTRODUCTION In recent times the continuing depletion of high grade mineral deposits and the massive increase in raw material consumption have forced the metal mining industry to exploit ore bodies of lower and lower grades. To obtain a satisfactory financial return from these deposits, there has been the concurrent and evident trend towards increasing the size of operations to obtain benefits from the economies of scale. The evaluation, planning, and design of these large scale open-pit operations, so as to yield the maximum possible return on investment, is an extremely complex, iterative procedure. With profit margins trimmed, "small" errors can become much more significant and with exploration costs spiralling, accurate and rapid evaluation is essential. It demands a sophistication and precision in the evaluation process unheard of ten years ago. What follows attempts to describe the need to thoroughly plan the overall evaluation programme such that duplication of effort is avoided and all relevant information is systematically recorded from the outset of exploration. The final section of the paper takes a realistic case study to illustrate the significance of pit slope angles on the design of the final pit and the economics of the total project. THE EVALUATION PROGRAMME The team, (for a team effort it must be), that is charged with the responsibility of conducting the evaluation exercise, has the difficult task of placing values on a multitude of independent and inter-related variables. Each variable has some economic significance; the degree of significance varying according to the metal sought, the environment in which it occurs, the vagaries of the market place, to name but a few of the problems facing the project team. From this maze of variables, the team must identify those that have the most critical influence on the overall economics of the proposed venture. Investigations must then be set in motion to quantify these controlling factors more precisely. It is important to recognize that such investigations form part of the evaluation programme and require monitoring for both timing and cost as the whole exercise of evaluating the project continues. To add to the difficulties, the economic significance of any particular variable may change during the course of the programme.

Jan 1, 1972

By Allan D. Fernie

Growing interest in pit crushing and conveying is evident from the many articles, technical papers, and new equipment development recently presented. Application of a pit crushing and conveying system is complex, as many factors such as mine design, production scheduling as well as initial and ongoing capital and operating costs must be thoroughly and realistically examined. This paper will address the fundamentals to be considered and review several approaches to developing a total system for a new and existing mine situation. The planning function will be outlined and operating and design criteria defined to interface the mining operation and the pit crushing conveying system.

Jan 1, 1983

By A. D. Fernie

Growing interest in pit crushing and conveying is evident from the recent many articles, technical papers, and new equipment development. Application of a pit crushing and conveying system is complex. Many factors, such as mine design, production scheduling, as well as initial and ongoing capital and operating costs must be thoroughly and realistically examined. This paper will address the fundamentals to be considered and review several approaches to developing a total system for a new and existing mine situation. The planning function will be outlined and operating and design criteria defined to interface the mining operation and the pit crushing conveying system.

Jan 1, 1986